Bankruptcy prediction has acquired great relevance for financial institutions
due to the complexity of global economies and the growing number of corporate
failures, especially since the world financial crisis of 2008. In this paper, the problem
of corporate bankruptcy prediction is faced by means of four linear classifiers (Fisher’s
linear discriminant, linear discriminant classifier, support vector machine and logistic
regression), which are designed on the dissimilarity space instead of the classical
feature space. Experimental results indicate that the prediction methods implemented
with the dissimilarity representation perform considerably better than the same tech

• Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction